13 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.LG2025
MatrixNet: Learning over symmetry groups using learned group representations
Lucas Laird, Circe Hsu, Asilata Bapat +1
Group theory has been used in machine learning to provide a theoretically grounded approach for incorporating known symmetry transformations in tasks from robotics to protein model…
math.CO2020★ 2 cited
Metric Dimension of Hamming Graphs and Applications to Computational Biology
Lucas Laird
Genetic sequencing has become an increasingly affordable and accessible source of genomic data in computational biology. This data is often represented as -mers, i.e., strings o…
cs.DM2019★ 13 cited
Resolvability of Hamming Graphs
Lucas Laird, Richard C. Tillquist, Stephen Becker +1
A subset of vertices in a graph is called resolving when the geodesic distances to those vertices uniquely distinguish every vertex in the graph. Here, we characterize the resolvab…